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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Automated feature selection for a machine learning approach toward modeling a mosquito distribution
Ralf Wieland, Antje Kerkow, Linus Früh, et al.
Ecological Modelling (2017) Vol. 352, pp. 108-112
Closed Access | Times Cited: 23

Showing 23 citing articles:

Hyperparameter tuning and performance assessment of statistical and machine-learning algorithms using spatial data
Patrick Schratz, Jannes Muenchow, Eugenia Iturritxa, et al.
Ecological Modelling (2019) Vol. 406, pp. 109-120
Open Access | Times Cited: 424
Review of machine learning techniques for mosquito control in urban environments
Ananya Joshi, Clayton Miller
Ecological Informatics (2021) Vol. 61, pp. 101241-101241
Open Access | Times Cited: 74
Machine learning in crop yield modelling: A powerful tool, but no surrogate for science
Gunnar Lischeid, Heidi Webber, Michael Sommer, et al.
Agricultural and Forest Meteorology (2021) Vol. 312, pp. 108698-108698
Open Access | Times Cited: 73
Decision support system for adaptive sourcing and inventory management in small- and medium-sized enterprises
Siravat Teerasoponpong, Apichat Sopadang
Robotics and Computer-Integrated Manufacturing (2021) Vol. 73, pp. 102226-102226
Closed Access | Times Cited: 63
Trends in mosquito species distribution modeling: insights for vector surveillance and disease control
Catherine A. Lippi, Stephanie J. Mundis, Rachel Sippy, et al.
Parasites & Vectors (2023) Vol. 16, Iss. 1
Open Access | Times Cited: 25
Correcting for the effects of class imbalance improves the performance of machine-learning based species distribution models
Donald J. Benkendorf, Samuel D. Schwartz, D. Richard Cutler, et al.
Ecological Modelling (2023) Vol. 483, pp. 110414-110414
Open Access | Times Cited: 23
A simulation-optimization approach for adaptive manufacturing capacity planning in small and medium-sized enterprises
Siravat Teerasoponpong, Apichat Sopadang
Expert Systems with Applications (2020) Vol. 168, pp. 114451-114451
Closed Access | Times Cited: 45
Modelling the potential distribution of an invasive mosquito species: comparative evaluation of four machine learning methods and their combinations
Linus Früh, Helge Kampen, Antje Kerkow, et al.
Ecological Modelling (2018) Vol. 388, pp. 136-144
Open Access | Times Cited: 40
Delimiting cryptic morphological variation among human malaria vector species using convolutional neural networks
Jannelle Couret, Danilo Coura Moreira, Davin Bernier, et al.
PLoS neglected tropical diseases (2020) Vol. 14, Iss. 12, pp. e0008904-e0008904
Open Access | Times Cited: 33
What makes the Asian bush mosquito Aedes japonicus japonicus feel comfortable in Germany? A fuzzy modelling approach
Antje Kerkow, Ralf Wieland, Marcel B. Koban, et al.
Parasites & Vectors (2019) Vol. 12, Iss. 1
Open Access | Times Cited: 34
Biotic Yield Losses in the Southern Amazon, Brazil: Making Use of Smartphone-Assisted Plant Disease Diagnosis Data
Anna Hampf, Claas Nendel, Simone Strey, et al.
Frontiers in Plant Science (2021) Vol. 12
Open Access | Times Cited: 23
Combined climate and regional mosquito habitat model based on machine learning
Ralf Wieland, Katrin Kuhls, Hartmut H. K. Lentz, et al.
Ecological Modelling (2021) Vol. 452, pp. 109594-109594
Open Access | Times Cited: 21
Modelling tree canopy cover and evaluating the driving factors based on remotely sensed data and machine learning
Anıl Akın, Ahmet Çilek, Ariane Middel
Urban forestry & urban greening (2023) Vol. 86, pp. 128035-128035
Closed Access | Times Cited: 8
Habitat Potential Mapping of Marten (Martes flavigula) and Leopard Cat (Prionailurus bengalensis) in South Korea Using Artificial Neural Network Machine Learning
Saro Lee, Sunmin Lee, Wonkyong Song, et al.
Applied Sciences (2017) Vol. 7, Iss. 9, pp. 912-912
Open Access | Times Cited: 18
Can data from native mosquitoes support determining invasive species habitats? Modelling the climatic niche of Aedes japonicus japonicus (Diptera, Culicidae) in Germany
Antje Kerkow, Ralf Wieland, Linus Früh, et al.
Parasitology Research (2019) Vol. 119, Iss. 1, pp. 31-42
Open Access | Times Cited: 12
Evaluating the efficiency of future crop pattern modelling using the CLUE-S approach in an agricultural plain
Anıl Akın, Nurdan Erdoğan, Süha Berberoğlu, et al.
Ecological Informatics (2022) Vol. 71, pp. 101806-101806
Closed Access | Times Cited: 7
Landscapes, Their Exploration and Utilisation: Status and Trends of Landscape Research
Lothar Mueller, Frank Eulenstein, Wilfried Mirschel, et al.
Innovations in landscape research (2019), pp. 105-164
Closed Access | Times Cited: 7
Linking a compartment model for West Nile virus with a flight simulator for vector mosquitoes
Antje Kerkow, Ralf Wieland, Jörn Gethmann, et al.
Ecological Modelling (2021) Vol. 464, pp. 109840-109840
Open Access | Times Cited: 4
Distributed and automated machine learning in big data stream analytics
Oraib H. Alsahlee, Abdallah Al-Zu'bi, Ibrahim I. Alamro, et al.
(2019) Vol. 2, pp. 307-313
Closed Access | Times Cited: 2
What makes the difference between memory and face of a landscape? A machine learning approach applied to the federal state Brandenburg, Germany
Ralf Wieland, Monika Wulf, Kristin Meier
Spatial Information Research (2018) Vol. 27, Iss. 2, pp. 237-246
Closed Access | Times Cited: 1
Interpretable machine learning approach to analyze the effects of landscape and meteorological factors on mosquito occurrences in Seoul, South Korea
Dae‐Seong Lee, Da‐Yeong Lee, Young‐Seuk Park
Environmental Science and Pollution Research (2022) Vol. 30, Iss. 1, pp. 532-546
Open Access | Times Cited: 1
Modeling and stochastic simulation to study the dynamics of Rickettsia rickettsii in populations of Hydrochoerus hydrochaeris and Amblyomma sculptum in the State of São Paulo, Brazil
Gina Polo
(2017)
Open Access
Learning spatial inequalities: an approach to support transportation planning.
Juliana Siqueira Gay
(2018)
Open Access
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